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<h1 class="title">Encoder Renishaw Vionic - Test Bench</h1>
<div id="table-of-contents">
<h2>Table of Contents</h2>
<div id="text-table-of-contents">
<ul>
<li><a href="#org691fd8d">1. Encoder Model</a></li>
<li><a href="#org6d49234">2. Noise Measurement</a>
<ul>
<li><a href="#orga5ff56c">2.1. Test Bench</a></li>
<li><a href="#org14877fe">2.2. Results</a></li>
</ul>
</li>
<li><a href="#org2b0bcde">3. Linearity Measurement</a>
<ul>
<li><a href="#org175ba6f">3.1. Test Bench</a></li>
<li><a href="#org69056ec">3.2. Results</a></li>
</ul>
</li>
<li><a href="#org5ca0c03">4. Dynamical Measurement</a>
<ul>
<li><a href="#orgde9a37d">4.1. Test Bench</a></li>
<li><a href="#org8bc51db">4.2. Results</a></li>
</ul>
</li>
</ul>
</div>
</div>
<hr>
<p>This report is also available as a <a href="./test-bench-vionic.pdf">pdf</a>.</p>
<hr>
<div class="note" id="org978e8ad">
<p>
You can find below the document of:
</p>
<ul class="org-ul">
<li><a href="doc/L-9517-9678-05-A_Data_sheet_VIONiC_series_en.pdf">Vionic Encoder</a></li>
<li><a href="doc/L-9517-9862-01-C_Data_sheet_RKLC_EN.pdf">Linear Scale</a></li>
</ul>
</div>
<p>
We would like to characterize the encoder measurement system.
</p>
<p>
In particular, we would like to measure:
</p>
<ul class="org-ul">
<li>Power Spectral Density of the measurement noise</li>
<li>Bandwidth of the sensor</li>
<li>Linearity of the sensor</li>
</ul>
<div id="orgf372152" class="figure">
<p><img src="figs/encoder_vionic.png" alt="encoder_vionic.png" />
</p>
<p><span class="figure-number">Figure 1: </span>Picture of the Vionic Encoder</p>
</div>
<ul class="org-ul">
<li>1: 2YA275</li>
<li>2: 2YA274</li>
<li>3: 2YA273</li>
<li>4: 2YA270</li>
<li>5: 2YA272</li>
<li>6: 2YA271</li>
<li>7: 2YJ313</li>
</ul>
<div id="outline-container-org691fd8d" class="outline-2">
<h2 id="org691fd8d"><span class="section-number-2">1</span> Encoder Model</h2>
<div class="outline-text-2" id="text-1">
<p>
The Encoder is characterized by its dynamics \(G_m(s)\) from the &ldquo;true&rdquo; displacement \(y\) to measured displacement \(y_m\).
Ideally, this dynamics is constant over a wide frequency band with very small phase drop.
</p>
<p>
It is also characterized by its measurement noise \(n\) that can be described by its Power Spectral Density (PSD).
</p>
<p>
The model of the encoder is shown in Figure <a href="#orgb6cf5b4">2</a>.
</p>
<div id="orgb6cf5b4" class="figure">
<p><img src="figs/encoder-model-schematic.png" alt="encoder-model-schematic.png" />
</p>
<p><span class="figure-number">Figure 2: </span>Model of the Encoder</p>
</div>
<p>
We can also use a transfer function \(G_n(s)\) to shape a noise \(\tilde{n}\) with unity ASD as shown in Figure <a href="#orgd00343b">4</a>.
</p>
<div id="org2725c4b" class="figure">
<p><img src="figs/encoder-model-schematic-with-asd.png" alt="encoder-model-schematic-with-asd.png" />
</p>
</div>
<table id="org20632fc" border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">
<caption class="t-above"><span class="table-number">Table 1:</span> Characteristics of the Vionic Encoder</caption>
<colgroup>
<col class="org-left" />
<col class="org-center" />
<col class="org-center" />
</colgroup>
<thead>
<tr>
<th scope="col" class="org-left"><b>Characteristics</b></th>
<th scope="col" class="org-center"><b>Manual</b></th>
<th scope="col" class="org-center"><b>Specifications</b></th>
</tr>
</thead>
<tbody>
<tr>
<td class="org-left">Range</td>
<td class="org-center">Ruler length</td>
<td class="org-center">&gt; 200 [um]</td>
</tr>
<tr>
<td class="org-left">Resolution</td>
<td class="org-center">2.5 [nm]</td>
<td class="org-center">&lt; 50 [nm rms]</td>
</tr>
<tr>
<td class="org-left">Sub-Divisional Error</td>
<td class="org-center">\(< \pm 15\,nm\)</td>
<td class="org-center">&#xa0;</td>
</tr>
<tr>
<td class="org-left">Bandwidth</td>
<td class="org-center">To be checked</td>
<td class="org-center">&gt; 5 [kHz]</td>
</tr>
</tbody>
</table>
<div id="orgd00343b" class="figure">
<p><img src="./figs/vionic_expected_noise.png" alt="vionic_expected_noise.png" />
</p>
<p><span class="figure-number">Figure 4: </span>Expected interpolation errors for the Vionic Encoder</p>
</div>
</div>
</div>
<div id="outline-container-org6d49234" class="outline-2">
<h2 id="org6d49234"><span class="section-number-2">2</span> Noise Measurement</h2>
<div class="outline-text-2" id="text-2">
<p>
<a id="org4cb96c9"></a>
</p>
</div>
<div id="outline-container-orga5ff56c" class="outline-3">
<h3 id="orga5ff56c"><span class="section-number-3">2.1</span> Test Bench</h3>
<div class="outline-text-3" id="text-2-1">
<p>
To measure the noise \(n\) of the encoder, one can rigidly fix the head and the ruler together such that no motion should be measured.
Then, the measured signal \(y_m\) corresponds to the noise \(n\).
</p>
</div>
</div>
<div id="outline-container-org14877fe" class="outline-3">
<h3 id="org14877fe"><span class="section-number-3">2.2</span> Results</h3>
<div class="outline-text-3" id="text-2-2">
<p>
First we load the data.
</p>
<div class="org-src-container">
<pre class="src src-matlab"><span class="org-matlab-cellbreak"><span class="org-comment">%% Load Data</span></span>
enc1 = load(<span class="org-string">'noise_meas_100s_20kHz_1.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'x'</span>);
enc2 = load(<span class="org-string">'noise_meas_100s_20kHz_2.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'x'</span>);
enc3 = load(<span class="org-string">'noise_meas_100s_20kHz_3.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'x'</span>);
enc4 = load(<span class="org-string">'noise_meas_100s_20kHz_4.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'x'</span>);
enc6 = load(<span class="org-string">'noise_meas_100s_20kHz_6.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'x'</span>);
enc7 = load(<span class="org-string">'noise_meas_100s_20kHz_7.mat'</span>, <span class="org-string">'t'</span>, <span class="org-string">'x'</span>);
</pre>
</div>
<p>
The raw measured data as well as the low pass filtered data (using a first order low pass filter with a cut-off at 10Hz) are shown in Figure <a href="#org72fd239">5</a>.
</p>
<div id="org72fd239" class="figure">
<p><img src="figs/vionic_noise_raw_lpf.png" alt="vionic_noise_raw_lpf.png" />
</p>
<p><span class="figure-number">Figure 5: </span>Time domain measurement (raw data and low pass filtered data with first order 10Hz LPF)</p>
</div>
<p>
The time domain data for all the encoders are compared in Figure <a href="#orgf7f2fda">6</a>.
</p>
<div id="orgf7f2fda" class="figure">
<p><img src="figs/vionic_noise_time.png" alt="vionic_noise_time.png" />
</p>
<p><span class="figure-number">Figure 6: </span>Comparison of the time domain measurement</p>
</div>
<p>
The amplitude spectral density is computed and shown in Figure <a href="#orgf3c083c">7</a>.
</p>
<div id="orgf3c083c" class="figure">
<p><img src="figs/vionic_noise_asd.png" alt="vionic_noise_asd.png" />
</p>
<p><span class="figure-number">Figure 7: </span>Amplitude Spectral Density of the measured signal</p>
</div>
<p>
Let&rsquo;s create a transfer function that approximate the measured noise of the encoder.
</p>
<div class="org-src-container">
<pre class="src src-matlab">Gn_e = 1.8e<span class="org-type">-</span>11<span class="org-type">/</span>(1 <span class="org-type">+</span> s<span class="org-type">/</span>2<span class="org-type">/</span><span class="org-constant">pi</span><span class="org-type">/</span>1e4);
</pre>
</div>
<p>
The amplitude of the transfer function and the measured ASD are shown in Figure <a href="#org8714af7">8</a>.
</p>
<div id="org8714af7" class="figure">
<p><img src="figs/vionic_noise_asd_model.png" alt="vionic_noise_asd_model.png" />
</p>
<p><span class="figure-number">Figure 8: </span>Measured ASD of the noise and modelled one</p>
</div>
</div>
</div>
</div>
<div id="outline-container-org2b0bcde" class="outline-2">
<h2 id="org2b0bcde"><span class="section-number-2">3</span> Linearity Measurement</h2>
<div class="outline-text-2" id="text-3">
<p>
<a id="orgc339bfd"></a>
</p>
</div>
<div id="outline-container-org175ba6f" class="outline-3">
<h3 id="org175ba6f"><span class="section-number-3">3.1</span> Test Bench</h3>
<div class="outline-text-3" id="text-3-1">
<p>
In order to measure the linearity, we have to compare the measured displacement with a reference sensor with a known linearity.
An interferometer or capacitive sensor should work fine.
An actuator should also be there so impose a displacement.
</p>
<p>
One idea is to use the test-bench shown in Figure <a href="#org30ec1c0">9</a>.
</p>
<p>
The APA300ML is used to excite the mass in a broad bandwidth.
The motion is measured at the same time by the Vionic Encoder and by an interferometer (most likely an Attocube).
</p>
<p>
As the interferometer has a very large bandwidth, we should be able to estimate the bandwidth of the encoder if it is less than the Nyquist frequency that can be around 10kHz.
</p>
<div id="org30ec1c0" class="figure">
<p><img src="figs/test_bench_encoder_calibration.png" alt="test_bench_encoder_calibration.png" />
</p>
<p><span class="figure-number">Figure 9: </span>Schematic of the test bench</p>
</div>
</div>
</div>
<div id="outline-container-org69056ec" class="outline-3">
<h3 id="org69056ec"><span class="section-number-3">3.2</span> Results</h3>
</div>
</div>
<div id="outline-container-org5ca0c03" class="outline-2">
<h2 id="org5ca0c03"><span class="section-number-2">4</span> Dynamical Measurement</h2>
<div class="outline-text-2" id="text-4">
<p>
<a id="org71dc40b"></a>
</p>
</div>
<div id="outline-container-orgde9a37d" class="outline-3">
<h3 id="orgde9a37d"><span class="section-number-3">4.1</span> Test Bench</h3>
</div>
<div id="outline-container-org8bc51db" class="outline-3">
<h3 id="org8bc51db"><span class="section-number-3">4.2</span> Results</h3>
</div>
</div>
</div>
<div id="postamble" class="status">
<p class="author">Author: Dehaeze Thomas</p>
<p class="date">Created: 2021-02-03 mer. 11:20</p>
</div>
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